The Explanatory Filter:
A three-part filter for understanding how to separate
and identify cause from intelligent design

An excerpt from a paper presented at the 1996 Mere Creation
conference, originally titled "Redesigning Science."

William A. Dembski, Ph.D.
Center for the Philosophy of Religion, University of Notre Dame

What is science going to look like once Intelligent Design
succeeds? To answer this question we need to be clear what we
mean by Intelligent Design. Intelligent Design is not repackaged
creationism, nor religion masquerading as science. Intelligent
Design holds that intelligent causation is an irreducible feature
of the bio-physical universe, and furthermore that intelligent
causation is empirically detectable. It is unexceptionable that
intelligent causes can do things which unintelligent causes cannot.
Intelligent Design provides a method for distinguishing between
intelligent and unintelligent causes, and then applies this method
to the special sciences.

Hardly a dubious innovation, Intelligent Design formalizes
and makes precise something we do all the time. All of us are
all the time engaged in a form of rational activity which, without
being tendentious, can be described as inferring design. Inferring
design is a perfectly common and well-accepted human activity.
People find it important to identify events that are caused through
the purposeful, premeditated action of an intelligent agent, and
to distinguish such events from events due to either law or chance.
Intelligent Design unpacks the logic of this everyday activity,
and applies it to questions in science. There's no magic, no vitalism,
no appeal to occult forces here. Inferring design is widespread,
rational, and objectifiable. The purpose of this paper is to formulate
Intelligent Design as a scientific theory.

The key step in formulating Intelligent Design as a scientific
theory is to delineate a method for detecting design. Such a method
exists, and in fact, we use it implicitly all the time. The method
takes the form of a three-stage Explanatory Filter. Given something
we think might be designed, we refer it to the filter. If it successfully
passes all three stages of the filter, then we are warranted asserting
it is designed. Roughly speaking the filter asks three questions
and in the following order: (1) Does a law explain it? (2) Does
chance explain it? (3) Does design explain it?

To see how the filter works in practice, consider the case
of Nicholas Caputo. Back in 1985 Nicholas Caputo was brought before
the New Jersey Supreme Court. The Republican party had filed suit
against him, claiming Caputo had consistently rigged the ballot
line in Essex County, New Jersey where he was county clerk. It
is a known fact that first position on a ballot increases one's
chances of winning an election. Since in every instance but one
Caputo positioned the Democrats first on the ballot line, the
Republicans argued that in selecting the order of ballots Caputo
had intentionally favored his own Democratic party. In short,
the Republicans claimed Caputo had cheated.

The question then before the New Jersey Supreme Court was,
Did Caputo actually rig the order, or was it without malice and
forethought on his part that the Democrats happened 40 out of
41 times to appear first on the ballot? Since Caputo denied wrongdoing,
and since he conducted the drawing of ballots so that witnesses
were unable to observe how he actually did draw the ballots, determining
whether Caputo did in fact rig the order of ballots becomes a
matter of evaluating the circumstantial evidence connected with
this case. How then is this evidence to be evaluated?

In determining how to explain the remarkable coincidence of
Nicholas Caputo selecting the Democrats 40 out of 41 times to
head the ballot line, the court had three options to consider:

LawUnbeknownst to Caputo, he was not employing a reliable random
process to determine ballot order. Caputo was in the position
of someone who thinks she is flipping a fair coin when in fact
she is flipping a double-headed coin. Just as flipping a double-headed
coin is going to yield a long string of heads, so Caputo, using
his faulty method for ballot selection, generated a long string
of Democrats coming out on top.

ChanceIn selecting the order of political parties on the state ballot,
Caputo employed a reliable random process that did not favor one
political party over another. The fact that the Democrats came
out on top 40 out of 41 times was simply a fluke. It occurred
by chance.

DesignCaputo, knowing full well what he was doing and intending
to aid his own political party, purposely rigged the ballot line
selection process so that the Democrats would consistently come
out on top. In short, Caputo cheated.

The first option-that Caputo chose poorly his procedure for
selecting ballot lines, so that instead of genuinely randomizing
the ballot order, it just kept putting the Democrats on top-was
dismissed by the court because Caputo himself had claimed to use
a randomization procedure in selecting ballot lines. And since
there was no reason for the court to think that Caputo's randomization
procedure was at fault, the key question therefore became whether
Caputo actually put this procedure into practice when he made
the ballot line selections, or whether he purposely circumvented
this procedure in order for the Democrats consis- tently to come
out on top. And since Caputo's actual drawing of the capsules
was obscured to witnesses, it was this question that the court
had to answer.

With the law explanation eliminated, the court next decided
to dispense with the chance explanation. Having noted that the
chances of picking the same political party 40 out of 41 times
were less than 1 in 50 billion, the court concluded that "confronted
with these odds, few persons of reason will accept the explanation
of blind chance." Now this certainly seems right. Nevertheless,
a bit more needs to be said. The problem is that the exceeding
improbability is by itself not enough to preclude something from
happening by chance.

Invariably, what is needed to eliminate chance is that the
event in question conform to a pattern. Not just any pattern
will do, however. Some patterns can legitimately be employed to
eliminate chance whereas others cannot.

A bit of terminology will prove helpful here. The "good"
patterns will be called specifications. Specifications
are the non-ad hoc patterns that can legitimately be used
to eliminate chance and warrant a design inference. In contrast,
the "bad" patterns may be called fabrications.
Fabrications are the ad hoc patterns that cannot legitimately
be used to eliminate chance.

By selecting the Democrats to head the ballot 40 out of 41
times, Caputo appears to have participated in an event of probability
less than 1 in 50 billion. Yet, exceedingly improbable things
happen all the time. The crucial question therefore is whether
this event is also specified-does this event follow a non-ad
hoc pattern so that we can legitimately eliminate chance?
But of course, the event is specified: that Caputo is a Democrat,
that it is in Caputo's interest to see the Democrats appear first
on the ballot, that Caputo controls the ballot lines, and that
Caputo would by chance be expected to assign Republicans top ballot
line as often as Democrats all conspire to specify Caputo's ballot
line selections, and render his selections incompatible with chance.
No one to whom I have shown this example draws any other conclusion
than design, to wit, Caputo cheated.

In the trial of Nicholas Caputo the New Jersey Supreme Court
employed the Explanatory Filter, first rejecting a law explanation,
then a chance explanation, and finally inferring a design explanation.

At the first stage, the filter determines whether a law can
explain the thing in question. Law thrives on replicability, yielding
the same result whenever the same antecedent conditions are fulfilled.
Clearly, if something can be explained by a law, it better not
be attributed to design. Things explainable by a law are therefore
eliminated at the first stage of the Explanatory Filter.

Suppose, however, that something we think might be designed
cannot be explained by any law. We then proceed to the second
stage of the filter. At this stage the filter determines whether
the thing in question might not reasonably be expected to occur
by chance. What we do is posit a probability distribution, and
then find that our observations can reasonably be expected on
the basis of that probability distribution. Accordingly, we are
warranted attributing the thing in question to chance. And clearly,
if something can be explained by reference to chance, it better
not be attributed to design. Things explainable by chance are
therefore eliminated at the second stage of the Explanatory Filter.

Suppose finally that no law is able to account for the thing
in question, and that any plausible probability distribution that
might account for it does not render it very likely. Indeed, suppose
that any plausible probability distribution that might account
for it renders it exceedingly unlikely. In this case we bypass
the first two stages of the Explanatory Filter and arrive at the
third and final stage. It needs to be stressed that this third
and final stage does not automatically yield design-there is still
some work to do. Vast improbability only purchases design if,
in addition, the thing we are trying to explain is specified.

The third stage of the Explanatory Filter therefore presents
us with a binary choice: attribute the thing we are trying to
explain to design if it is specified; otherwise, attribute it
to chance. In the first case, the thing we are trying to explain
not only has small probability, but is also specified. In the
other, it has small probability, but is unspecified. It is this
category of specified things having small probability that reliably
signals design. Unspecified things having small probability, on
the other hand, are properly attributed to chance.

The Explanatory Filter faithfully represents our ordinary practice
of sorting through things we alternately attribute to law, chance,
or design. In particular, the filter describes

how copyright and patent offices identify theft of intellectual
property

how insurance companies prevent themselves from getting ripped
off

how detectives employ circumstantial evidence to incriminate
a guilty party

how forensic scientists are able reliably to place individuals
at the scene of a crime

how skeptics debunk the claims of parapsychologists

how scientists identify cases of data falsification

how NASA's SETI program seeks to identify the presence of extra-
terrestrial life, and

how statisticians and computer scientists distinguish random
from non-random strings of digits.

Entire industries would be dead in the water without the Explanatory
Filter. Much is riding on it. Using the filter, our courts have
sent people to the electric chair. Let us now see why the filter
works.

Why the Filter Works

The filter is a criterion for distinguishing intelligent from
unintelligent causes. Here I am using the word "criterion"
in its strict etymological sense as a method for deciding or judging
a question. The Explanatory Filter is a criterion for deciding
when something is intelligently caused and when it isn't. Does
it decide this question reliably?

As with any criterion, we need to make sure that whatever judgments
the criterion renders correspond to reality. A criterion for judging
the quality of wines is worthless if it judges the rot-gut consumed
by winos superior to a fine French Bordeaux. The reality is that
a fine French Bordeaux is superior to the wino's rot-gut, and
any criterion for discriminating among wines better indicate as
much.

Or consider medical tests. Any medical test is a criterion.
A perfectly reliable medical test would detect the presence of
a disease whenever it is indeed present, and fail to detect the
disease whenever it is absent. Unfortunately, no medical test
is perfectly reliable, and so the best we can do is keep the proportion
of false positives and false negatives as low as possible.

All criteria, and not just medical tests, face the problem
of false positives and false negatives. A criterion attempts to
classify individuals with respect to a target group (in the case
of medical tests, those who have a certain disease). When the
criterion classifies an individual who should not be there in
the target group, it commits a false positive. Alternatively,
when the criterion fails to classify an individual who should
be there in the target group, it commits a false negative. Take
medical tests again. A medical test checks whether an individual
has a certain disease. The target group comprises all those individuals
who actually have the disease. When the medical test classifies
an individual who doesn't have the disease with those who do,
it commits a false positive. When the medical test classifies
an individual who does have the disease with those who do not,
it commits a false negative.

When the Explanatory Filter fails to detect design in a thing,
can we be sure no intelligent cause underlies it? The answer to
this question is No. For determining that something is not designed,
the Explanatory Filter is not a reliable criterion. False negatives
are a problem for the Explanatory Filter. This problem of false
negatives, however, is endemic to detecting intelligent causes.
One difficulty is that intelligent causes can mimic law and chance,
thereby rendering their actions indistinguishable from these unintelligent
causes. It takes an intelligent cause to know an intelligent cause,
but if we don't know enough, we'll miss it.

Intelligent causes can do things that unintelligent causes
cannot, and can make their actions evident. When for whatever
reason an intelligent cause fails to make its actions evident,
we may miss it. But when an intelligent cause succeeds in making
its actions evident, we take notice. This is why false negatives
do not invalidate the Explanatory Filter. The Explanatory Filter
is fully capable of detecting intelligent causes intent on making
their presence evident.

And this brings us to the problem of false positives. Even
though the Explanatory Filter is not a reliable criterion for
eliminating design, it is, I argue, a reliable criterion
for detecting design. The Explanatory Filter is a net.
Things that are designed will occasionally slip past the net.
We would prefer that the net catch more than it does, omitting
nothing due to design. But given the ability of design to mimic
unintelligent causes and the possibility of our own ignorance
passing over things that are designed, this problem cannot be
fixed. Nevertheless, we want to be very sure that whatever the
net does catch includes only what we intend it to catch, to wit,
things that are designed.

I argue that the explantory filter is a reliable criterion
for detecting design. Alternatively, I argue that the Explanatory
Filter successfully avoids false positives. Thus whenever the
Explanatory Filter attributes design, it does so correctly.

Let us now see why this is the case. I offer two arguments.
The first is a straightforward inductive argument: in every instance
where the Explanatory Filter attributes design, and where the
underlying causal story is known, it turns out design actually
is present; therefore, design actually is present whenever the
Explanatory Filter attributes design.

My second argument for showing that the Explanatory Filter
is a reliable criterion for detecting design may now be summarized
as follows: the Explanatory Filter is a reliable criterion for
detecting design because it coincides with how we recognize intelligent
causation generally. In general, to recognize intelligent causation
we must observe a choice among competing possibilities, note which
possibilities were not chosen, and then be able to specify the
possibility that was chosen.

The Relevance to Biology

One thing is clear. Creationists and evolutionists alike feel
the force of design. At some level they are all responding to
it. This is true even of those who, unlike Dawkins, think that
life is extremely unlikely to occur by chance in the known physical
universe, but who nevertheless agree with Dawkins that life is
properly explained without reference to design. Here I have in
mind advocates of the Anthropic Principle, like Barrow and Tipler
(1986), who posit an ensemble of universes so that life, though
highly improbable in our own little universe, is nevertheless
virtually certain to have arisen at least once in the many- many
universes that constitute the ensemble of which our universe is
a member. This move allows Barrow and Tipler to vastly multiply
their probabilistic resources, and thus vastly lower their probability
for the origin of life on earth.

There remain other ways to block design in explaining life.
Some theorists think our own little universe is quite enough to
render life not only probable, but virtually certain. Stuart Kauffman,
for instance, identifies life with "the emergence of self-reproducing
systems of catalytic polymers, either peptides, RNA, or others"
(The Origins of Order,1993, p.340). Adopting this theoretical
perspective, Kauffman develops a mathematical model in which "autocatalytic
polymer sets . . . are expected to form spontaneously" (p.288).
Kauffman is attempting to lay the foundation for a theory of life's
origin in which life is not a lucky accident, but an event that
is to be fully expected:

I believe [life] to be an expected, emergent, collective property
of complex systems of polymer catalysts. Life, I suggest, 'crystallizes'
in a phase transition leading to connected sequences of biochemical
transformations by which polymers and simpler building blocks
mutually catalyze their collective reproduction (p.287).

Kauffman is in effect explaining life in terms of law. Thus
with respect to the Explanatory Filter, Kauffman need never proceed
beyond even the first decision node. Kauffman is not alone in
explaining life in terms of law. Prigogine and Stengers (1984,
pp. 84,176), Wicken (1987), and Brooks and Wiley (1988) all share
this same commitment with Kauffman.

In sum, whereas creationists justify design as the proper mode
for explaining life by arguing that the relevant probabilities
are sufficiently small, evolutionary biologists reject design
by arguing that the relevant probabilities never quite get small
enough. Thus Darwin, to prevent the probabilities from getting
too small, had to give himself more time for variation and selection
to take effect than many of his contemporaries were willing to
grant (cf. Lord Kelvin, who as the leading physicist in Darwin's
day estimated the age of the earth at 100 million years, even
though Darwin regarded this age as too low to be consonant with
his theory). Thus Dawkins, to prevent the probabilities from getting
too small, not only gives himself all the time Darwin ever wanted,
but also helps himself to all the conceivable planets there might
be in the known physical universe. Thus Barrow and Tipler, to
prevent the probabilities from getting too small, not only give
themselves all the time and planets that Dawkins ever wanted,
but also help themselves to a generous serving of universes (universes
which are by definition causally inaccessible to us). Thus Kauffman,
to prevent the probabilities from getting too small, conjectures
laws of self- organization according to which life will almost
surely arise spontaneously on a planet like ours. From the perspective
of the Explanatory Filter, all of these moves have but one purpose:
to block the conclusion that the proper mode of explanation for
life is design.

Bill Dembski, one of the organizers of the Mere Creation conference,
has a Ph.D. in mathematics and philosophy, and an M.Div. from
Princeton Theological Seminary. As a visiting scholar at Notre
Dame, Dembski is investigating the foundations of design.